Simple implementation of the ConvergenceChecker interface using
only objective function values.
Convergence is considered to have been reached if either the relative
difference between the objective function values is smaller than a
threshold or if either the absolute difference between the objective
function values is smaller than another threshold.
The converged
method will also return true if the number of iterations has been set
(see this constructor).

SimpleValueChecker

Build an instance with specified thresholds.
In order to perform only relative checks, the absolute tolerance
must be set to a negative value. In order to perform only absolute
checks, the relative tolerance must be set to a negative value.

Parameters:

relativeThreshold - relative tolerance threshold

absoluteThreshold - absolute tolerance threshold

SimpleValueChecker

Builds an instance with specified thresholds.
In order to perform only relative checks, the absolute tolerance
must be set to a negative value. In order to perform only absolute
checks, the relative tolerance must be set to a negative value.

converged

Check if the optimization algorithm has converged considering the
last two points.
This method may be called several time from the same algorithm
iteration with different points. This can be detected by checking the
iteration number at each call if needed. Each time this method is
called, the previous and current point correspond to points with the
same role at each iteration, so they can be compared. As an example,
simplex-based algorithms call this method for all points of the simplex,
not only for the best or worst ones.